CN116743219B - Symbol-level precoding method and system for non-orthogonal multiple access communication system - Google Patents
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- H04B7/00—Radio transmission systems, i.e. using radiation field
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Abstract
The invention relates to the technical field of wireless communication, and provides a symbol-level precoding method and system for a non-orthogonal multiple access communication system, wherein the applied communication system comprises a communication system provided with N t And each base station simultaneously transmits information to K user terminals. The symbol-level precoding method comprises the following steps: modulating information bits sent to a user terminal by a base station through phase shift keying to obtain data symbols; establishing a relation model between a base station symbol level precoding signal and a user terminal SINR; determining constraint conditions according to the relation model, and constructing an optimization target for the total transmitting power of the base station; solving an approximate solution of the optimization target based on an iterative optimization algorithm to obtain a precoding matrix; and carrying out symbol-level precoding by utilizing the precoding matrix to obtain a precoding signal.
Description
Technical Field
The present invention relates to the field of wireless communication technologies, and in particular, to a symbol level precoding method and system for a non-orthogonal multiple access communication system.
Background
At present, the demands for high throughput, ultra-low time delay and ultra-large connection of a wireless communication system are continuously increased, and the available frequency bandwidth of the wireless communication system is limited, so that the frequency spectrum utilization efficiency is improved in the communication process, and the system performance can be obviously improved. In contrast, the present communication system mainly uses the orthogonal multiple access technology for data transmission, and the non-orthogonal multiple access technology is one of the key technologies of the physical layer of the wireless communication system due to its high spectral efficiency, large-scale connectivity and lower receiver complexity.
The non-orthogonal multiple access is mainly divided into a power domain and a code domain, the power domain non-orthogonal multiple access uses superposition coding technology at a transmitting end, and a receiving end uses SIC (Symbol Level Precoding, serial interference cancellation) technology to assist demodulation. However, the limitation is also remarkable, if the number of users sharing the spectrum increases, the number of SIC operations of non-orthogonal multiple access becomes large, the complexity of the receiver is very high, and the performance of communication is still limited by diversified interference in the wireless communication scenario. The precoding technique not only can ensure the service requirement, but also can effectively manage interference, so that a great deal of research is developed on the non-orthogonal multiple access and precoding technique, and interference among users is eliminated by utilizing the precoding technique, such as SLP (Symbol Level Precoding ) technique. However, the interference nature is not considered in the application of the SLP technology at present, and the problem of low energy utilization rate of the system exists in the simple interference elimination.
Disclosure of Invention
The invention provides a symbol-level precoding method and a system for a non-orthogonal multiple access communication system, which are used for overcoming the defect of low system energy utilization rate in the application of the SLP technology in the non-orthogonal multiple access communication system in the prior art.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a symbol-level precoding method for a non-orthogonal multiple access communication system uses a communication system comprising a plurality of N-equipped communication systems t And each base station simultaneously transmits information to K user terminals.
The symbol-level precoding method comprises the following steps:
modulating information bits sent to a user terminal by a base station through phase shift keying to obtain data symbols;
establishing a relation model between a base station symbol level precoding signal and a user terminal SINR;
determining constraint conditions according to the relation model, and constructing an optimization target for the total transmitting power of the base station;
solving an approximate solution of the optimization target based on an iterative optimization algorithm to obtain a precoding matrix;
and carrying out symbol-level precoding by utilizing the precoding matrix to obtain a precoding signal.
Furthermore, the invention also provides a symbol-level precoding system oriented to the non-orthogonal multiple access communication system, and the symbol-level precoding method provided by the invention is applied. The communication system to which the method is applied comprises a communication system provided with N t And each base station simultaneously transmits information to K user terminals.
The symbol-level precoding system comprises:
the modulation module is used for modulating information bits sent to the user terminal by the base station through phase shift keying to obtain data symbols;
the power optimization module is provided with a relation model between a base station symbol level precoding signal and a user terminal SINR and constraint conditions determined according to the relation model; the power optimization module is used for constructing an optimization target for the total transmitting power of the base station;
the data processing module is used for solving an approximate solution of the optimization target based on an iterative optimization algorithm and outputting a precoding matrix;
and the precoding module is used for carrying out symbol-level precoding according to the precoding matrix and outputting a precoding signal.
Furthermore, the invention also provides a computer device, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the symbol-level precoding method.
Further, the present invention also proposes a storage medium having stored thereon computer readable instructions which, when executed by a processor, implement the steps of the symbol-level precoding method proposed by the present invention.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that: the invention carries out symbol-level precoding design on the data at the transmitting end, constructs an optimization target for the total transmitting power of the base station by ensuring the constraint condition determined by the correct demodulation requirement of the user with stronger non-orthogonal multiple access channel gain, converts the non-convex constraint in the constraint condition into the convex constraint, converts the non-convex constraint into the convex constraint, and solves the optimization problem by adopting an iterative optimization method, thereby obtaining a precoding matrix which is used for precoding the signal at the transmitting end, converting the interference of the strong user to the weak user into the energy beneficial to signal detection, realizing the communication method of effective management of the interference in the non-orthogonal multiple access communication, and simultaneously realizing the realization of meeting the performance of a wireless communication system, reducing the whole power consumption and improving the spectrum efficiency of the wireless communication system.
Drawings
Fig. 1 is a flowchart of a symbol-level precoding method of embodiment 1.
Fig. 2 is a diagram of the architecture of a non-orthogonal multiple access communication system of embodiment 1.
Fig. 3 is a graph of transmit power optimization versus different channel differences for example 1.
Fig. 4 is a diagram of the architecture of the symbol-level precoding system of embodiment 2.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the present patent; for a better description of the present embodiments, it will be understood that some well-known descriptions may be omitted from the accompanying drawings.
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Example 1
The present embodiment proposes a symbol-level precoding method for a non-orthogonal multiple access communication system, as shown in fig. 1, which is a flowchart of the symbol-level precoding method of the present embodiment.
The symbol-level precoding method for the non-orthogonal multiple access communication system provided by the embodiment comprises the following steps:
s1, modulating information bits sent to a user terminal by a base station through phase shift keying to obtain data symbols.
S2, establishing a relation model between the base station symbol level precoding signal and the SINR of the user terminal.
S3, determining constraint conditions according to the relation model, and constructing an optimization target for the total transmitting power of the base station.
And S4, solving an approximate solution of the optimization target based on an iterative optimization algorithm to obtain a precoding matrix.
S5, carrying out symbol-level precoding by utilizing the precoding matrix to obtain a precoding signal.
In a multiple user downlink non-orthogonal multiple access scheme, a communication system includes a base station configured with N t And each base station simultaneously transmits information to K user terminals.
In this embodiment, symbol-level precoding design is performed on data at a transmitting end, an optimization target is constructed on total transmitting power of a base station by ensuring a constraint condition determined by correct demodulation requirements of users with strong non-orthogonal multiple access channel gains, non-convex constraints in the constraint condition are converted into convex constraints, and then the optimization problem is solved by adopting an iterative optimization method, so that the obtained precoding matrix is used for precoding signals at the transmitting end, interference of strong users on weak users is converted into energy beneficial to signal detection, and a communication method for effectively managing interference in non-orthogonal multiple access communication is realized.
In an alternative embodiment, the relation model between the base station symbol level pre-coded signal and the SINR of the user terminal includes:
if the symbol-level precoding is performed at the base station side, the expression of SINR received by the user terminal i is:
wherein, gamma' i Represents the SINR received by user terminal i, and i e {1,2, -1}; h is a i Representing a channel vector from the base station to the user terminal i; w (w) k Representing symbol-level precoding signal vectors from the base station to the user terminal k,symbol phase representing user terminal k +.>Representing the symbol phase, s, of the user terminal 1 1 Representing the modulated signal transmitted by the user terminal 1;is the additive white gaussian noise variance for user terminal i.
In the present embodiment, let s i Representing a modulated signal transmitted by user terminal i, where i e {1, 2., }. The signal is selected from a MPSK (multiple phase shift keying, multi-system digital phase modulation) constellation having a unit amplitude, whereby the received signal y of the user terminal i i Expressed as:
wherein n is i Representing additive white gaussian noise at user terminal i. The arrangement in this embodimentInstantaneous transmit power P at the base station side t The definition is as follows:
further, in this embodiment, it is assumed that the channel gain intensities for the pairs are arranged in ascending order by the index numbers of the users, for example:this indicates that user 2 is a cell center user and user 1 is at the cell edge. In the conventional non-orthogonal multiple access communication model, the symbols of all strong users are regarded as unknown interference by the user 1, for example, the symbols of the users 2 to K, and the user 1 decodes the symbols directly, so the SINR when the user 1 receives can be expressed as:
from the above equation, the weakest user 1 is interfered by all strong users. The present embodiment will apply SLP technology at the base station to convert the interference of strong users to it into beneficial interference. For the second weakest user 2, it first decodes the symbols of the weakest user 1 by treating the symbols of other strong users as harmful interference; secondly, the user 2 will cancel the part of the user 1 in the received signal; finally, it decodes the desired symbol from the remainder.
Meanwhile, in order to avoid error propagation, the present embodiment requires that the user 2 can successfully decode the symbol of the user 1. Thus, the SINR of user 2 in the SIC procedure is expressed as:
through the above operation, the SINR at the time of decoding by the user 2 can be expressed as:
the present embodiment will validate the SLP technique when the user 2 demodulates its own information. Similarly, at the strongest user K, the SIC decodes the weaker symbols of users 1 through K-1 first, at which time the SINR of user K during the SIC process can be expressed as:
after all SIC is completed, the SNR (signal-to-noise ratio) of user K is:
if the downlink channel information and all user data are known at the transmitting end, pre-processing data symbols at the base station sideThe coding may convert the multi-user interference into a portion of the useful signal energy through symbol level operation. Specifically, by precoding matrix [ w 1 ,w 2 ,...,w K ]Alignment interference designs synthesize a beneficial signal, thereby negatively affecting weak users by strong users, e.g., gamma 1 ，γ 2 And gamma K The multiuser interference in the denominator term when decoding the information is converted into useful energy for signal detection.
Therefore, by applying the SLP technique at the base station side in this embodiment, the SINR received by the users 1 to K-1 can be expressed as:
in this embodiment, interference caused by a user with a stronger channel gain will become energy contributing to signal reception, and the SLP constraint that needs to be satisfied is:
wherein,representing the imaginary part of the complex number, +.>Representing the real part of the complex number, Γ i SNR for minimum Qos requirement for user terminal i, phi is maximum angular offset in constructive interference region, and +.>M is the modulation order.
In an alternative embodiment, the constraints include SIC constraints, SLP constraints determined by channel state information (Channel State Information, CSI) of the user terminals and data symbols in the relationship model, and Qos requirements of all user terminals.
In this embodiment, the total transmit power of the base station of the system is optimized by ensuring the SIC constraint of correct demodulation of the users with stronger non-orthogonal multiple access channel gain, the SLP constraint determined by the CSI and data symbols of the users known to the base station, and the Qos of all the users.
Further, in an alternative embodiment, when an optimization target is constructed for the total transmission power of the base station, the optimization target is constructed with the objective of minimizing the total transmission power of the base station, where the expression is as follows:
wherein the first constraint is an SLP constraint, representing a minimum distance between the region of constructive interference and the correct detection region;representing the imaginary part of the complex number, +.>Representing the real part of the complex number, Γ i SNR for minimum Qos requirement for user terminal i, phi is maximum angular offset in constructive interference region, and +.>M is the modulation order; the second constraint indicates that successful SIC should be satisfied when strong users decode symbol data of weak usersConstraint; the third constraint represents minimum Qos requirements for the kth user,/for the kth user>Representing the additive white gaussian noise variance of the user terminal k.
Further, in an alternative embodiment, solving an approximate solution of the optimization objective under non-convex constraints based on an iterative optimization algorithm comprises:
and converting the optimization target into an approximate SOCP (second order cone planning) problem through an approximation method, converting constraint into SOC constraint, and solving the optimization target converted into the approximate SOCP problem by utilizing a convex optimization tool to obtain an approximate solution of the optimization target.
Wherein the optimization objective translated into an approximate SOCP problem is expressed as:
||[2 K ,(h-1)] H ||≤h+1
wherein:
in sigma j Representing the standard deviation of the additive white gaussian noise of the user terminal j.
In this embodiment, a taylor approximation method is introduced to convert the non-convex target problem into a resolvable convex problem, where, in order to find an optimal solution, the non-convex problem of minimizing the base station transmitting power can be further converted into a convex problem, where the channel state information of the channel and the data information of the user are known. The present embodiment adopts an approximation method for the second and third constraints, and approximates the first-order taylor expansion of the function at a certain point to two real-valued functions, and the following inequality exists after expansion:
then, the non-convex constraint of the original problem can be converted into a convex constraint by substituting the above formula, and z is a constraint due to hyperbola 2 The presence of +.xy (x +.0, y +.0) results in +.2, x-y] H The hold of the +.x+y constraint, these approximated convex constraints can be converted to SOC constraints.
From the above-described deduction, the original problem of the present embodiment can be converted into an SOCP problem, which is a convex problem and can be effectively solved by using an existing convex optimization tool.
Further, in an alternative embodiment, the approximate solution of the optimization objective is solved based on an iterative optimization algorithm. The method comprises the following steps:
selecting a precoding vector from solutions satisfying all constraints of the optimization target as an initial pointAnd updated in each iteration;
according toSaid optimization objective solving the problem of converting into an approximated SOCP, obtaining an optimized +.>Wherein the precoding vector obtained for each optimization will be a fixed point for the next iteration, n representing the iterationThe times of generation;
repeating the steps until the maximum iteration times are met or the increment value of the optimization target is smaller than a preset threshold value epsilon, and then exiting iteration to obtain an optimal solution w * 。
As an exemplary illustration, the preset threshold value in the present embodiment is set to e=10 -5 The method comprises the steps of carrying out a first treatment on the surface of the The maximum number of iterations is set to 30.
Further, the precoding matrix is utilized to perform symbol-level precoding, and a precoding signal combination is obtained. The expression is as follows:
wherein,representing the optimal symbol-level precoding signal vector from the base station to the kth user terminal, s K Representing the modulated signal transmitted by the kth user terminal.
In this embodiment, the inequality relation of the first-order taylor approximation is utilized to convert the non-convex constraint into the convex constraint, the inequality derived relation is utilized to rewrite the convex constraint into the SOC constraint, and finally the optimal solution is obtained by finding out the initial point of the problem and repeatedly iterating and optimizing the mode.
As an exemplary illustration, as shown in fig. 2, an architecture diagram of the non-orthogonal multiple access communication system of the present embodiment is shown. Including a base station with 2 transmit antennas and 4 single antenna users, in which the base station knows the channel state information of the users and the transmitted data signals.
The present embodiment uses the index number of the user to rank up the channel gain strengths for use, e.gThis indicates that user 4 is the cell center user, while user 1 is at the cell edge, the weakest user 1 is interfered by all strong users.
The present embodiment applies SLP technology at the base station side so that multi-user interference encountered when users 1 to 3 decode their symbols becomes beneficial. Through the SIC constraint of ensuring correct demodulation of users with stronger non-orthogonal multiple access channel gain, the SLP constraint determined by CSI and data symbols of users known by a base station, and Qos of all users, the total transmitting power of a system base station is optimized, a Taylor approximation method is further introduced to convert a non-convex target problem into a resolvable convex problem, then the approximate solution of the base station transmitting power optimization problem under the non-convex constraint is solved based on the proposed iterative optimization algorithm, and finally the precoding signal is calculated by utilizing the solved precoding matrix.
As shown in fig. 3, a transmission power optimization and a different channel difference comparison simulation diagram of the method of the present embodiment and the conventional non-orthogonal multiple access scheme are shown. As can be seen from the figure, the base station transmitting power of the method of the embodiment is far lower than that of the conventional scheme under the condition of the same SINR, and it is obvious that the method of the embodiment can effectively improve the system energy utilization rate, meet the performance of the wireless communication system, and simultaneously reduce the overall power consumption and improve the spectrum efficiency of the wireless communication system.
Example 2
The present embodiment proposes a symbol-level precoding system for a non-orthogonal multiple access communication system, and applies the symbol-level precoding method of embodiment 1. As shown in fig. 4, an architecture diagram of the symbol-level precoding system of the present embodiment is shown.
The communication system to which the present embodiment is applied includes a communication system equipped with N t And each base station simultaneously transmits information to K user terminals.
The symbol-level precoding system provided in this embodiment includes:
and the modulation module is used for modulating information bits sent to the user terminal by the base station through phase shift keying to obtain data symbols.
The power optimization module is provided with a relation model between a base station symbol level precoding signal and a user terminal SINR and constraint conditions determined according to the relation model; the power optimization module is used for constructing an optimization target for the total transmitting power of the base station.
And the data processing module is used for solving the approximate solution of the optimization target based on an iterative optimization algorithm and outputting a precoding matrix.
And the precoding module is used for carrying out symbol-level precoding according to the precoding matrix and outputting a precoding signal.
In an alternative embodiment, the relationship model set in the power optimization module is expressed as:
wherein, gamma' i Represents the SINR received by user terminal i, and i e {1,2, -1}; h is a i Representing a channel vector from the base station to the user terminal i; w (w) k Representing symbol-level precoding signal vectors from the base station to the user terminal k,representing the phase of the user terminal k symbol, +.>Representing the phase of the symbol of user terminal 1 s 1 Representing the modulated signal transmitted by the user terminal 1;is the additive white gaussian noise variance for user terminal i. Wherein the symbol-level precoding is set to be performed at the base station side.
Further optionally, the constraint conditions set in the power optimization module include SIC constraint, SLP constraint determined by channel state information and data symbols of the user terminals in the relationship model, and Qos requirements of all the user terminals.
Further optionally, when the power optimization module constructs an optimization target for the total transmission power of the base station, the power optimization module constructs the optimization target with the objective of minimizing the total transmission power of the base station. The expression is as follows:
wherein the first constraintFor SLP constraints, representing a minimum distance between the constructive interference zone and the correct detection zone; />Representing the imaginary part of the complex number, +.>Representing the real part of the complex number, Γ i SNR for minimum Qos requirement for user terminal i, phi is maximum angular offset in constructive interference region, and +.>M is the modulation order; the second constraint represents the constraint that a successful SIC should satisfy when a strong user decodes the symbol data of a weak user; the third constraint represents the minimum Qos requirement for the kth user.
Further optionally, the data processing module solves an approximate solution of the optimization target under a non-convex constraint based on an iterative optimization algorithm, specifically, converts the optimization target into an approximate SOCP problem through an approximation method, converts a constraint into an SOC constraint, and solves the optimization target converted into the approximate SOCP problem by utilizing a convex optimization tool to obtain an approximate solution of the optimization target.
Further alternatively, the data processing module solves for an approximate solution of the optimization objective based on an iterative optimization algorithm, specifically selecting a precoding vector as an initial point from solutions satisfying all constraints of the optimization objectiveAnd updated in each iteration; according to->Solving the optimization objective of the SOCP problem converted into approximation to obtain an optimizationWherein the precoding vector obtained for each optimization will be the fixed point for the next iteration; repeating the steps until the maximum iteration times are met or the increment value of the optimization target is smaller than a preset threshold value, and then exiting the iteration to obtain an optimal solution w * 。
Further optionally, the precoding module performs symbol-level precoding on the precoding matrix to obtain a precoded signal combinationWherein (1)>Representing the optimal symbol-level precoding signal vector from the base station to the kth user terminal, s K Representing the modulated signal transmitted by the kth user terminal.
Example 3
The present embodiment proposes a computer device comprising a memory and a processor, the memory storing computer readable instructions that, when executed by the processor, cause the processor to perform the steps of the symbol-level precoding method as proposed in embodiment 1.
Example 4
The present embodiment proposes a storage medium having stored thereon computer readable instructions which, when executed by a processor, implement the steps of the symbol-level precoding method as proposed in embodiment 1.
The terms describing the positional relationship in the drawings are merely illustrative, and are not to be construed as limiting the present patent;
it is to be understood that the above examples of the present invention are provided by way of illustration only and not by way of limitation of the embodiments of the present invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are desired to be protected by the following claims.
Claims (9)
1. A symbol-level precoding method for a non-orthogonal multiple access communication system, characterized in that the communication system comprises a base station equipped with N t Base stations of the transmitting antennas, each base station simultaneously transmitting information to K user terminals; wherein:
modulating information bits sent to a user terminal by a base station through phase shift keying to obtain data symbols;
establishing a relation model between a base station symbol-level pre-coding signal and a user terminal signal-to-interference-plus-noise ratio SINR;
the relation model between the base station symbol level pre-coding signal and the SINR of the user terminal comprises the following steps:
if the symbol-level precoding is performed at the base station side, the expression of SINR received by the user terminal i is:
wherein, gamma' i Representing SINR received by user terminal i, and i e {1,2,., K-1}; h is a i Representing a channel vector from the base station to the user terminal i; w (w) k Representing symbol-level precoding signal vectors from the base station to the user terminal k,symbol phase representing user terminal k +.>Representing the symbol phase, s, of the user terminal 1 1 Representing the modulated signal transmitted by the user terminal 1; />An additive white gaussian noise variance for user terminal i;
determining constraint conditions according to the relation model, and constructing an optimization target for the total transmitting power of the base station;
solving an approximate solution of the optimization target based on an iterative optimization algorithm to obtain a precoding matrix;
and carrying out symbol-level precoding by utilizing the precoding matrix to obtain a precoding signal.
2. The symbol-level precoding method of claim 1 wherein the constraint conditions comprise successive interference cancellation, SIC, constraint, symbol-level precoding, SLP, constraint determined by channel state information and data symbols of user terminals in the relational model, and Qos requirements of all user terminals.
3. The symbol-level precoding method as claimed in claim 2, wherein when the optimization target is constructed for the total transmission power of the base station, the optimization target is constructed with the objective of minimizing the total transmission power of the base station, and the expression is:
wherein the first constraintFor SLP constraints, representing a minimum distance between the constructive interference zone and the correct detection zone; />Representing the imaginary part of the complex number, +.>Representing the real part of the complex number, Γ i Signal-to-noise ratio, SNR, for minimum Qos requirement of user terminal i, phi is the maximum angular offset in the constructive interference zone, and +.>M is the modulation order; the second constraint represents the constraint that a successful SIC should satisfy when a strong user decodes the symbol data of a weak user; the third constraint represents minimum Qos requirements for the kth user,/for the kth user>Representing the additive white gaussian noise variance of the user terminal k.
4. A symbol-level precoding method as claimed in claim 3, characterized in that said solving an approximate solution of said optimization objective under non-convex constraint based on an iterative optimization algorithm comprises:
converting the optimization target into an approximate second-order cone planning (SOCP) problem through an approximation method, converting constraint into a second-order cone System On Chip (SOC) constraint, and solving the optimization target converted into the approximate SOCP problem by utilizing a convex optimization tool to obtain an approximate solution of the optimization target; wherein the optimization objective translated into an approximate SOCP problem is expressed as:
||[2σ K ,(h-1)] H ||≤h+1
wherein:
in sigma j Representing the standard deviation of the additive white gaussian noise of the user terminal j.
5. The symbol-level precoding method as claimed in claim 4, wherein the solving the approximate solution of the optimization objective based on the iterative optimization algorithm comprises:
selecting a precoding vector from solutions satisfying all constraints of the optimization target as an initial pointAnd updated in each iteration;
according toSaid optimization objective solving the problem of converting into an approximated SOCP, obtaining an optimized +.>Wherein the precoding vector obtained by each optimization is a fixed point of the next iteration, and n represents the number of iterations;
repeating the steps until the maximum iteration times are met or the increment value of the optimization target is smaller than a preset threshold value, and then exiting the iteration to obtain an optimal solution w * 。
6. The symbol-level precoding method as claimed in any one of claims 1-5, characterized in that the precoding matrix is utilized for symbol-level precoding to obtain a precoding signal combination; the expression is as follows:
wherein,representing the optimal symbol-level precoding signal vector from the base station to the kth user terminal, s K Representing the modulated signal transmitted by the kth user terminal.
7. Symbol-level precoding system for non-orthogonal multiple access communication system, application claimThe symbol-level precoding method as claimed in any one of 1 to 5, characterized in that the communication system comprises a carrier equipped with N t Base stations of the transmitting antennas, each base station simultaneously transmitting information to K user terminals; the symbol-level precoding system includes:
the modulation module is used for modulating information bits sent to the user terminal by the base station through phase shift keying to obtain data symbols;
the power optimization module is provided with a relation model between a base station symbol level precoding signal and a user terminal SINR and constraint conditions determined according to the relation model; the power optimization module is used for constructing an optimization target for the total transmitting power of the base station;
the data processing module is used for solving an approximate solution of the optimization target based on an iterative optimization algorithm and outputting a precoding matrix;
and the precoding module is used for carrying out symbol-level precoding according to the precoding matrix and outputting a precoding signal.
8. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the symbol-level precoding method of any of claims 1 to 5.
9. A storage medium having stored thereon computer readable instructions which when executed by a processor implement the steps of the symbol level precoding method as claimed in any one of claims 1 to 5.
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